A Case Study in Worker Wellness and Safety

Challenge

For years, efforts to deploy robotic automation to take over dangerous and harmful tasks for workers have over-promised and under-delivered. Industries seeking to protect and retain their employees implemented numerous robotic systems designed to tackle heavy and repetitive lifting, but each time they fell short or failed at these tasks, significant human intervention remained a requirement, putting workers right back into harm’s way, despite significant investments to avoid this.

What’s been holding them back? Substandard item detection, identification and prioritization; faulty information about item packaging, center of gravity, item obstruction; and more. These perception deficiencies result in frequent failed picks. While robots and grippers have long been capable of handling heavy objects, their muted success rates have been driven by lackluster vision software providing limited information.

Solution

AVT Europe NV – owned by Vinci Group – turned to Fizyr for advanced Vision AI to collect more and better data faster for improved accuracy, speed and reliability. In Fizyr’s vision AI, cascade learning is integrated throughout a three-step process that empowers a robot to receive critical information from an image and direct a robot to take the appropriate action with a gripper in milliseconds:

1. Identification: After a camera captures an image, Fizyr’s vision AI uses segmentation, shape detection and material detection to identify the task at hand.

   

2. Prioritization: Fizyr’s vision AI combines two-dimensional and three-dimensional data and uses sequencing to determine which items are on top of others. It also analyzes the surface of each item to locate the flattest, largest, sturdiest or otherwise most desirable surfaces with which to work. 
3. Robot communication: With a sophisticated plan of attack ready to accomplish the task at hand, Fizyr’s vision AI then sends instructions to the robot. These include pick positions, the proper angle of approach, selecting the right force and gripper options out of a set of configurations, and more. Fizyr Vision accounts for shifting contents within bags, providing the robot with an optimal grasp strategy when just ‘grabbing from the middle’ can cause damage or insecure grasps.

Integrating Fizyr’s Vision AI into its robotic cell for depalletizing unlocked AVT’s ability to pick and place heavy bags with great success, a task which had been considered impossible.

Results

Initially, AVT deployed multiple depalletizing robots for two different end users that pick and place heavy bags exceeding 25kg from variable pallet stacks at a rate of more than 400 bags per hour. Capable of reaching 1000 bags per hour, these robotic cells automate one of the most difficult and hard to staff jobs in the supply chain and provide a critical competitive advantage to food manufacturers and other dry goods processors. 

Following the success of the initial installations, AVT rolled out this solution to two new customers: Imprextraco, an animal feed company, and Katoen Natie, an international logistics service provider and port operator, signaling greater adoption by businesses seeking to effectively relieve workers of this dangerous task. 

See it in action here:

avt depallitization heavy bag depalletisation logistics automation vision ai